Data Movement Challenges and Solutions with Software Defined Networking.
Degree: PhD, Computer Engineering, 2017, Clemson University
With the recent rise in cloud computing, applications are routinely accessing and interacting with data on remote resources. Interaction with such remote resources for the operation of media-rich applications in mobile environments is also on the rise. As a result, the performance of the underlying network infrastructure can have a significant impact on the quality of service experienced by the user. Despite receiving significant attention from both academia and industry, computer networks still face a number of challenges. Users oftentimes report and complain about poor experiences with their devices and applications, which can oftentimes be attributed to network performance when downloading or uploading application data. This dissertation investigates problems that arise with data movement across computer networks and proposes novel solutions to address these issues through software defined networking (SDN). SDN is lauded to be the paradigm of choice for next generation networks. While academia explores use cases in various contexts, industry has focused on data center and wide area networks. There is a significant range of complex and application-specific network services that can potentially benefit from SDN, but introduction and adoption of such solutions remains slow in production networks. One impeding factor is the lack of a simple yet expressive enough framework applicable to all SDN services across production network domains. Without a uniform framework, SDN developers create disjoint solutions, resulting in untenable management and maintenance overhead. The SDN-based solutions developed in this dissertation make use of a common agent-based approach. The architecture facilitates application-oriented SDN design with an abstraction composed of software agents on top of the underlying network. There are three key components modern and future networks require to deliver exceptional data transfer performance to the end user: (1) user and application mobility, (2) high throughput data transfer, and (3) efficient and scalable content distribution. Meeting these key components will not only ensure the network can provide robust and reliable end-to-end connectivity, but also that network resources will be used efficiently. First, mobility support is critical for user applications to maintain connectivity to remote, cloud-based resources. Today's network users are frequently accessing such resources while on the go, transitioning from network to network with the expectation that their applications will continue to operate seamlessly. As users perform handovers between heterogeneous networks or between networks across administrative domains, the application becomes responsible for maintaining or establishing new connections to remote resources. Although application developers often account for such handovers, the result is oftentimes visible to the user through diminished quality of service (e.g. rebuffering in video streaming applications). Many intra-domain handover solutions exist for handovers…
Advisors/Committee Members: Dr. Kuang-Ching Wang, Committee Chair, Dr. Harlan Russell, Dr. Richard Brooks, Dr. Jim Martin.
Subjects/Keywords: data movement; network; openflow; software defined networking
to Zotero / EndNote / Reference
APA (6th Edition):
Izard, R. (2017). Data Movement Challenges and Solutions with Software Defined Networking. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1910
Chicago Manual of Style (16th Edition):
Izard, Ryan. “Data Movement Challenges and Solutions with Software Defined Networking.” 2017. Doctoral Dissertation, Clemson University. Accessed June 22, 2018.
MLA Handbook (7th Edition):
Izard, Ryan. “Data Movement Challenges and Solutions with Software Defined Networking.” 2017. Web. 22 Jun 2018.
Izard R. Data Movement Challenges and Solutions with Software Defined Networking. [Internet] [Doctoral dissertation]. Clemson University; 2017. [cited 2018 Jun 22].
Available from: https://tigerprints.clemson.edu/all_dissertations/1910.
Council of Science Editors:
Izard R. Data Movement Challenges and Solutions with Software Defined Networking. [Doctoral Dissertation]. Clemson University; 2017. Available from: https://tigerprints.clemson.edu/all_dissertations/1910